
The folder contains the data used to train PGNNIVs to unravel the go or grow behaviour of glioblastoma under 4 different parametric models. These data consist on the solutions (in time and space) of eleven simulations with different oxygen boundary conditions. Each folder is named as DATA_"ModelName", where "ModelName" can be: "Sigmoid", "ReLU", "MichaelisMenten" or "Heaviside". Inside each folder, the multidimensional arrays for input and output data for the network training can be found. These arrays have dimension [nExp,TimeStep,x,field], where: nExp = 11 and corresponds to the number of different configurations or experiments simulated. TimeStep = 1000 and correspond to the different temporal frames where the solution is given. x = 51 and corresponds to the different spatial points where the solution is given. field = 2 and correspond to the different solution fields (1: cells, 2: oxygen).
Physically-Guided Neural Networks with Internal Variables, glioblastoma, Physics-Informed Data Science
Physically-Guided Neural Networks with Internal Variables, glioblastoma, Physics-Informed Data Science
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